Journal Directory Related to Data Science

This blog contains a list of journals related to Data Science and Analytics:

  1. Japanese Journal of Statistics and Data Science, Springer
  2. 10 Essential Academic Journal for Data Scientists, Analytics India
  3. International Journal of Data Science and Analysis, Science Publishing Group
  4. International Journal of Data Science and Analytics, Springer
  5. Data Science Journal, CoData
  6. Journals, Magazine in Analytics, Big Data, Data Mining, and Knowledge Discovery, KDnuggets.com
  7. Data Science, IOS Press
  8. EPJ Data Science, Springernature.com
  9. International Journal of Data Science (IJDS), Inderssience publishers
  10. The Journal of Finance and Data Science, KeAi Chinese Roots Global Impact
  11. SIAM Journal on Mathematics of Data Science
  12. Data Science Journal, SJR
  13. ASA Data Science Journal
  14. Scientific Data, Nature.com
  15. Data Science: Methods, Infrastructure, and Applications
  16. Statistical Analysis and Data Mining, Wiley Online Library
  17. International Journal of Population Data Science (IJPDS)
  18. Earth System Science Data
  19. Archives of Data Science, Series A
  20. Oxford Journal of Intelligent Decision and Data Science
  21. Annual Reviews of Biomedical Data Science
  22. Practical Data Science for Stats -a Peer J Collection
  23. Data Science and Pattern Recognition
  24. Frontiers of Marketing Data Science Journal, i-com Global Forum for Marketing Data and Measurement
  25. ACM Transactions on Data Science (TDS), ACM Digital Library
  26. Advances in Data Science and Adaptive Analysis, World Scientific
  27. Top Journals and conference in Data Mining and Data Science, a blog
  28. Mathematics of Computation and Data Science
  29. Journal of Data Science and Its Applications
  30. Research Data Journal for the Humanities and Social Sciences
  31. Data Technologies and Applications, emerald Publishing
  32. Data Journal Directory
  33. Harvard and Elsevier Explore Collaborations in Data Science
  34. The Role of Statistics in Data Science-An ASA Statement
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A Bit History of Survival Analysis

In world history, it uses BC/AD dating system. What are the true meanings of  BC and AD?  You can find the answer at https://www.gotquestions.org/BC-AD.html

Who is the creator of life table?

Read http://www.stat.rice.edu/stat/FACULTY/courses/stat431/Graunt.pdf for answer.

What does life table do?

To estimate the survival probability of a life time variable.

Is it good estimator? Well it is simple. Kaplan-Meier proposed another one in 1958. But it still didn’t take covariates into consideration. Cox (1972) proposed the proportional hazards model and since then survival analysis in statistics is well formulated. But Cox PH model has several assumptions: 1. hazard ratio does not depend on time; 2. The lifetime data has one endpoint (event); 3. independent assumption; 4. interest in hazard ratio, not the length of life time. To overcome these limits, many more models have been proposed. To read on, read “Analysis of survival data: challenges and algorithm-based model selection “.  For more hands-on analysis using competing risks and multistate models, read here.

 

Data Science Programs

In the hype of Big Data Analytics and Data Science, how many college programs have been created in the past few years to meet the end market demand workforce? Is your school catching up with the trend of education?

To get some idea of the list of programs, one can visit the following webpages:

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